Cytokine-stimulated phosphorylation of GSK-3 is primarily dependent upon PKCs, not PKB
Bibliographic record
Abstract
The regulation of glycogen synthase kinase-3 (GSK-3) by phosphorylation at inhibitory sites has been well documented. In many, but not all, cases, the phosphatidylinositol 3-kinase pathway, and particularly the downstream kinase protein kinase B (PKB)/akt, have been shown to be responsible for GSK-3 phosphorylation. Given that no studies have ever reported cytokine-mediated phosphorylation of GSK-3, we investigated the phosphorylation of this kinase in several hemopoietic cell types in response to either interleukin (IL)-3, IL-4 or granulocyte-macrophage colony stimulating factor (GM-CSF). Each of the cytokines was able to stimulate phosphorylation of the isoforms GSK-3alpha and GSK-3beta. However, only in the case of IL-4 stimulation was there any dependence on PKB for this phosphorylation. We were clearly able to show that PKB was capable of phosphorylating GSK-3 in these cells, but studies using inhibitors of the protein kinase C (PKC) family of kinases have shown that these enzymes are more likely to play a key role in GSK-3 phosphorylation. Cytokine-mediated generation of diacylglycerol was demonstrated, supporting the possible activation of PKC family members. Thus, cytokine-dependent GSK-3 phosphorylation in hemopoietic cells proceeds primarily through PKB independent pathways.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".